Associate Research Scientist (PREP0004096) Part-time

Associate Research Scientist

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.

Research Title: Scientific Literature Data Extraction

The work will entail: The research associate will provide subject-matter expertise for developing, deploying, and testing an internal web-based application to assist researchers in conducting structured literature reviews of technical documents. The work involves designing and building a user-friendly interface for Scientific Literature Data Extraction, to be deployed for internal testing and validation at NIST. The research associate will focus on supporting the creation of a system that ensures transparency in data extraction and allows for customizable summary generation.

Key responsibilities will include but are not limited to:

• Provide guidance on vision.
• Support development, deployment, and evaluation of Scientific Literature Data Extraction interface.
• Strategic planning and management for ensuring project success.
• Presenting development progress and results at internal meetings.

Qualifications

A doctoral degree in Electrical Engineering, Computer Science, or a related field.

15+ years of relevant experience.

Experience automating complex systems through computer vision and machine learning as well as scientific/engineering simulation & visualization, predictive visual analytics, complex computer algorithm development, and computer network security.

Experience leading teams of researchers in bridging fundamental research and real-world application.

Familiarity with state-of-the art in multi-modal artificial intelligence.

Access to a research lab is a plus.

Familiarity with methods for structured literature reviews (e.g., PICO, PRISMA).

Strong oral and written communication skills.